RE-EVALUATION OF TRENDS AND CHANGES IN MEAN, MAXIMUM AND MINIMUM TEMPERATURES OF TURKEY FOR THE...

INTERNATIONAL JOURNAL OF CLIMATOLOGY

Int. J. Climatol. 22: 947–977 (2002)

Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/joc.777

RE-EVALUATION OF TRENDS AND CHANGES IN MEAN, MAXIMUM ANDMINIMUM TEMPERATURES OF TURKEY FOR THE PERIOD 1929–1999

MURAT TURKES,* UTKU M. SUMER and ISMAIL DEMIR

Turkish State Meteorological Service, Ankara, Turkey

Received 24 September 2001Revised 3 January 2002

Accepted 6 January 2002

ABSTRACT

Mean, maximum and minimum surface air temperatures recorded at 70 climatological stations in Turkey during theperiod from 1929 to 1999 were analysed to reveal spatial and temporal patterns of long-term trends, change points,significant warming (cooling) periods and linear trend rates per decade. Annual, winter and spring mean temperatureshave tended to increase, particularly over the southern regions of Turkey, whereas summer and particularly autumnmean temperatures have decreased over the northern and continental inner regions. Annual, winter, spring and summermaximum temperatures have indicated a positive trend at many stations, except those in the Central Anatolia and BlackSea regions and partly in the Eastern Anatolia region. Autumn maximum temperatures, however, have decreased slightlyover much of Turkey, except for the Aegean region. The majority of the urbanized and rapidly urbanizing stationsin Turkey have been experiencing an apparent night-time warming, especially during the warm and dry period of theyear. Minimum temperatures have shown a statistically significant positive trend at 31 stations annually, 30 stations inspring and 33 stations in summer; most are significant at the 0.01 level. Winter and autumn minimum temperatures haveindicated a general negative trend in some portions of the Marmara, Black Sea and Eastern Anatolia regions, whereas ageneral positive trend has been seen over much of Turkey along with the significant trends in the Mediterranean regionof the country.

Summer night-time warming rates are generally larger than in spring and autumn night-time temperatures. On theother hand, the night-time warming rates of spring and summer are generally stronger than those in spring and summerdaytime temperatures. By considering the marked increasing trends in spring, summer and annual minimum temperaturesof urban stations, we have recognized that this is a clear and significant indication for the existence of a strong night-timeurban warming in Turkey. Copyright 2002 Royal Meteorological Society.

KEY WORDS: Turkey; air temperature; urbanization; non-parametric tests; homogeneity; serial dependence; trend and trend rate;change point

1. INTRODUCTION

Human-induced climate change and changes in climatic variability continue to be major global change issuesnot only for the present generation but also for future generations. Based on the latest scientific assessmentof the Earth’s climate system, Folland et al. (2001) have revealed that average global surface temperature hasincreased by about 0.6 ± 0.2 °C since the late 19th century. The Northern Hemisphere experienced coolingduring the period from 1946 to 1975, while the Southern Hemisphere showed warming. They pointedout that the recent 1976–2000 warming was largely globally synchronous, but was more pronounced inthe Northern Hemisphere continents during winter and spring. Folland et al. (2001), by assessing a largenumber of studies, have also indicated that analyses of mean daily maximum and minimum land surface airtemperatures continued to support a decrease in the diurnal temperature ranges in many parts of the world.

* Correspondence to: Murat Turkes, Turkish State Meteorological Service, Department of Research, PO Box 401, Ankara, Turkey;e-mail: mturkes@meteor.gov.tr

948 M. TURKES, U. M. SUMER AND I. DEMIR

Minimum temperatures increased at nearly twice the rate of maximum temperatures during the period from1950 to 1993.

As an expected result of concern over climate change, there has been an increasing number of studiesin the last 10 years dealing with long-term surface air temperature variations and trends, and variationsand anomalies associated with circulation types across the Mediterranean basin, particularly for the easternbasin and individual countries (Metaxas et al., 1991; Arseni-Papadimitriou and Maheras, 1991; Esteban-Parra and Rodrigo, 1995; Turkes et al., 1995; Turkes et al., 1996; Kadıoglu, 1997; Proedrou et al., 1997;Tayanc et al., 1997; Kutiel and Maheras, 1998; Ben-Gai et al., 1999; Maheras et al., 1999; Price et al., 1999;Quereda Sala et al., 2000; etc.). The main findings and conclusions from some studies related to the easternMediterranean basin can be summarized as follows. Proedrou et al. (1997), based on annual and seasonaltemperatures determined from ground and satellite measurements, detected an overall cooling trend for themajority of Greek stations in winter for the entire period of 1951–93, and in annual and summer meantemperatures but up to the mid-1970s. They also showed that summer temperatures had a warming trendroughly after 1975 at most stations, and satellite measurements had an insignificant warming trend. Kutieland Maheras (1998) examined the temperature regime over the Mediterranean basin and the relationshipbetween temperature variations and circulation indices. For seasonal temperature trends, they used the data in22 grid boxes of 5° × 5° for the entire Mediterranean area and at six stations. They found a warming trend,which was more evident in the western Mediterranean than in the eastern Mediterranean. In another detailedstudy on circulation types over the Mediterranean basin, Maheras et al. (1999) showed the complexity of theMediterranean climate, especially the atmospheric driving forces of the temperature regime and anomalies.They confirmed the conclusions of the previous studies, that prevailing temperature conditions in the west-central Mediterranean basin were influenced by circulation over the Atlantic, whilst the eastern part of thebasin was subject to varying influences, dependent on circulation over southern Asia, North Africa, east-central Europe, and on season. Price et al. (1999) found, for two stations in Cyprus, an increasing trend witha rate of about 1 °C/100 years in annual mean temperatures. They showed minimum temperatures generallyincreased at a larger rate than maximum temperatures, resulting in a decrease in long-term diurnal temperaturerange. Ben-Gai et al. (1999) analysed the maximum and minimum temperatures of 40 stations in Israel for the1964–94 period. They revealed that both temperatures were characterized by a significant decreasing trendduring the cool season and by an increasing trend during the warm season.

Based on the results from previous studies (Turkes, 1995, 1996a; Turkes et al., 1995; Kadıoglu, 1997;Tayanc et al., 1997), a general decrease was dominant in annual and seasonal mean surface air temperatureseries over much of Turkey. In particular, the coastal regions of Turkey were generally characterized bycolder than long-term average temperature conditions during the period between the late 1960s and early1990s. The cooling tendency was particularly marked in summer mean temperatures. A general increasingtrend was evident in seasonal minimum temperature series over much of Turkey, and a general decreasing trendin maximum temperature series in all seasons, except spring, over much of Turkey (Turkes, 1996a; Turkeset al., 1996). A general decreasing trend was apparent in mean annual and seasonal global solar radiation data,particularly in annual, summer and autumn series, over most of Turkey during the 1960–94 period (Aksoy,1997). Aksoy (1997) attributed the decrease of the solar radiation to deterioration of air quality in Turkey.

Nevertheless, this situation has begun to change for about last 10 years in Turkey, particularly during thewarm period of the year (Erlat, 1998, 1999; Turkes, 2000). When we made a test study, it was pointed outthat previous results with cooling trends in mean and maximum temperature series have been weakeningand been less significant. This is due to the increases in the mean, maximum and minimum temperatureseries of Turkey during the last 10 years or so, particularly in spring and summer seasons. Consequently, wehave analysed the re-evaluated and updated data set of Turkish mean, maximum and minimum temperatureseries of 70 stations for a longer study period, from 1929 to 1999. The scope of the paper is: (i) to givedetailed information on the updated Turkish temperature data and homogeneity assessments of temperatureseries; (ii) to assess the rapid urbanization in Turkey; (iii) to reveal the nature and magnitude of the serialdependence and long-term trends, and the change points and significant warming (or cooling) periods inannual and seasonal mean, maximum and minimum temperature series of Turkey by using non-parametrictests; and (iv) to detect the linear trend rates per decade in the same temperature series.

TEMPERATURE TRENDS IN TURKEY 949

2. DATA AND ASSESSMENT OF HOMOGENEITY

This study is based on an updated temperature data set consisting of monthly averages of the daily mean, dailymaximum (daytime) and daily minimum (night-time) temperatures. Temperature data have been observed andrecorded by the Turkish State Meteorological Service (TSMS) since the late 1920s. We found some errorsin the monthly minimum temperature series at the very beginning of the study. These errors were identifieddirectly by checking the daily temperature records in the original climatological registers of the TSMS archive.The errors arose from the fact that negative signs of some daily minimum temperature values, in the monthsmostly from December to March, were omitted by mistake during the process of inputting daily records intothe TSMS database. The errors of sign in minimum temperatures of some stations, which are located over thecolder and continental central Anatolia and eastern Anatolia regions of Turkey, were corrected by using thedaily records in the original climatological registers. The corrections were also reflected in the TSMS database.

Temperature variations and trends for Turkey were re-analysed by using a newly updated data set includingmonthly averages of daily mean, maximum and minimum surface air temperatures. These temperature seriesof observations were recorded at stations of the TSMS, during the period 1929–99. Values for December1929 were used only for computing winter averages in the year of 1930. Selection of the stations was carriedout by taking into account the stations used in our previous studies (Turkes et al., 1995, 1996; Turkes, 1999).A total of 80 stations, of which 58 are common with Turkes et al. (1996), were re-examined with respectto their length of record, geographical distribution over Turkey and homogeneity. For the present study,inhomogeneity means non-climatological strong jumps (step-wise changes) in the mean of the series. Missingvalues in monthly temperature records were filled in by a simple approach. In the case of a monthly missingvalue, this was replaced by the 2 year monthly average centred on the missing month. The number of missingvalues that were filled in is less than 5% of all monthly values in a station’s selected study period. For thestudy, annual and seasonal average series were calculated from the monthly mean, monthly maximum andmonthly minimum series.

In order to detect homogeneity in mean annual and seasonal series, first a homogeneity analysis wasperformed by using the non-parametric Kruskal–Wallis (K–W) test for homogeneity was carried out ofthe means and variances (Sneyers, 1990; Turkes, 1996b; Turkes et al., 1996) of both 7- and 10-year sub-periods. The analysis was carried out for the means and variances of both 7 and 10-year sub-periods. Thisobjective analysis was done not only to detect inhomogeneity (inconsistency) in the overall series, but also toexamine whether the recent observations of about the last decade (in which increased spring and particularlysummer minimum temperatures were dominant at many stations) affected the consistency of the temperatureseries. Second, the non-parametric Wald–Wolfowitz (W–W) serial correlation test was applied to the series toexamine the nature and magnitude of the serial dependence from year-to-year variations, and/or abrupt changesin the series (Sneyers, 1990, 1992; Turkes, 1996b; Turkes et al., 1996). The result of the W–W test, whensupported by information from both a station’s history file and statistical and graphical time-series analyses,is very useful for deciding whether a statistically significant inhomogeneity in a series (especially with aprobability less than 0.01) arose from a non-climatological jump, from natural low-frequency fluctuations, ora strong persistence. A non-climatological jump in the mean of a series may result either from an abrupt changeassociated with relocation of a station or from a steep trend (a rapid increase or decrease) in temperaturevalues because of different factors, such as urbanization (i.e. urban heat island effect or urban cooling effectrespectively). Third, statistically significant inhomogeneities from the K–W test were checked by means ofthe additional information from our own station’s history file and the plotted time-series to some extent.Time-series plots were prepared for both original temperatures with smoothed values and the u(t) and u′(t)values derived from the sequential analysis of the Mann–Kendall (M–K) test.

Eighty stations were selected at the beginning for the purposes of homogeneity and the decision-makingstudy. The homogeneity assessments of the mean, maximum and minimum temperature series can besummarized as follows.

The K–W test has revealed some seasonal variations, particularly for the minimum temperatures. Accordingto the results from the K–W test, most annual mean, maximum and minimum temperature series have beenfound to be homogeneous with respect to the homogeneity of both means and variances of 7 and 10 year

length sub-periods. Winter mean, maximum and minimum temperature series at all stations are homogeneous.There is neither any significant jump nor any apparent long-period fluctuation in the winter temperatureseries.

Most of the spring and summer mean and maximum temperature series are homogeneous with respectto both non-climatological jumps in the means and changes in the variances. Nevertheless, approximatelyhalf of the spring minimum temperature series, most of which are characterized by a significant secularincreasing trend, seem to be inhomogeneous, although there is no non-climatological marked jump in theseseries. Indeed, it is clear that very rapid and significant increasing trends are the prevalent behaviour withrespect to long-term variations of the spring minimum temperatures. Time-series plots of the spring minimumtemperatures have also proved that series of most stations, even in the different geographical regions ofTurkey, are considerably similar to each other in terms of the year-to-year variability, long-period fluctuationand trend patterns (Figures 9 and 10).

It has been realized, from the non-randomness characteristics of the climatic series, that the summerminimum temperature series are the most striking series in Turkey. According to the statistical tests, summerminimum temperature series are not random either against the homogeneity and persistence or against thesecular trend. Most series seem to be inhomogeneous and their year-to-year variability is mostly characterizedby a significant positive serial correlation coefficient. In fact, long-term variations in summer minimumtemperatures of these stations are explained either with a significant secular increasing trend or with arapid increase over the last 10 to 20 year period (Figure 13). Consequently, we recognize that the large(significant) test statistics from the K–W test showing inhomogeneity for the spring and summer minimumtemperature series are very much likely associated with rapid and significant increases in the means of thoseseries.

Most autumn mean, maximum and minimum temperature series are also random with respect to bothnon-climatological jumps in the means and changes in the variances.

By using all types of climatological assessments mainly based on the statistical analyses and the station’shistory information, along with numbers of missing values and length of records, ten of the 80 stations wereextracted from the study. Three of the ten stations taken out of the study had experienced station relocationfrom an inland site to the coast or to a site nearer to a coastal area than that of its previous location. Thesestations, namely Fethiye, Antalya and Anamur, are located in the western and middle sub-regions of Turkey’sMediterranean coastal belt. We found significant inhomogeneities at those relocated stations in terms of thelong-term variations and trends in temperature series. In particular, the relocations of the Fethiye and Anamurstations in 1962, from inner parts of the cities to their present sites near the coast and just on the coastrespectively, created an artificial cooling effect on temperature measurements throughout the year comparedwith the observations previous to 1962. For instance, in Fethiye, a non-climatological step-wise decrease wasdetected in the annual (Figure 1) and seasonal (not shown here) mean, maximum and minimum temperatures.This non-natural cooling effect, which appears to be stronger during the warmer part of the year, is verylikely to be associated with land and especially sea breezes, which are the dominant local wind circulation inthe spring, summer and autumn months on the Mediterranean coast of Turkey (Turkes, 1999). The main non-randomness characteristics of the temperature series observed at a relocated station are that these series showalmost the same trend behaviour in all months and seasons, such as very significant decreasing (increasing)trend statistics for almost all months and seasons. In other words, the sign and magnitude of the trends inthose series do not depict any natural inter-seasonal differences after the relocation occurred, because theartificial cooling (warming) effect of the station’s relocation has suppressed the natural variability and inparticular the trend characteristics of the temperature series at that station.

Finally, the temperature series from 70 principal climatological stations found to be homogeneous werechosen for re-analysing and re-evaluating the long-term variations and trends in the Turkish temperature seriesduring the period from 1929 to 1999. Of the 70 stations, 56 (80%) stations have a length of record in the period1930–41 and 14 (20%) stations in the period 1942–62. Consequently, by taking into account the fact thatofficial climatological observations at many of the Turkish stations started in the late 1920s, an approximately60–70 year observation period at 80% of the selected 70 stations can be accepted as relatively sufficient. Thespatial distributions of the geographical regions and the locations of the 70 stations in Turkey are shown in

b. Mean temperature trend

1930 1940 1950 1960 1970 1980 1990 2000

d. Maximum temperature trend

1930 1940 1950 1960 1970 1980 1990 2000

f. Minimum temperature trend

−6−4−20246

1930 1940 1950 1960 1970 1980 1990 2000

c. Maximum temperature variations

1930 1940 1950 1960 1970 1980 1990 2000

1962 Relocation of station

a. Mean temperature variations

1930 1940 1950 1960 1970 1980 1990 2000

1962 Relocation of station

e. Minimum temperature variations

9101112131415

1930 1940 1950 1960 1970 1980 1990 2000

) 1962 Relocation of station

Figure 1. Variations and trends in annual mean, maximum and minimum temperature series of Fethiye: (a), (c), (e) interannual variationswith smoothed line by the Binomial filter ( ) with padded ends, long-term average X ( ), and averages of sub-periods(- - - - ) before (X1) and after (X2) 1962; (b), (d), (f) trends from sequential values of the statistics u(t) ( ) and u′(t) (–ž–) of

the M–K test, with critical value of ±1.96 at the 0.05 level of significance (- - - - )

Figure 2. Stations are well distributed, not only across the country but also across the geographical regions ofTurkey; the exceptions are the western Mediterranean coast, Eastern Anatolia region and the inner portion ofthe eastern Black Sea. This is mainly due to inhomogeneous series related to the relocation of some coastalstations for the Mediterranean region, and a greater number of missing values and shorter record lengths forstations of the Eastern Anatolia region and eastern Black Sea sub-region.

3. URBANIZATION IN TURKEY

Turkey is one of the rapidly urbanizing countries in the developing countries of the world. According tothe results of the 1997 census (DIE, 1997), the population of Turkey increased from 56 473 035 in 1990to 62 865 574 in 1997, with a 15.08‰ annual rate of increase during the period 1990–97. Of this totalpopulation (de facto), 40 882 357 settled in cities (centres of provinces and districts), whereas 21 983 217settled in villages. The annual rate of population increase is 28.27‰ for centres of provinces and districts,and −6.57‰ for villages. From the 1997 census, the share of the total population in centres of provincesand districts is 65.03%, and in villages it is 34.97%. In the 1990 census, these proportions were 59.21%and 40.79% respectively. The city population of Turkey in 1997 increased by 5.82% compared with the citypopulation in 1990. Population increased in all geographical regions except around the Black Sea during the

0 50 100km

B L A C K S E A

M E D I T E R R A N E A N

12131416

212226

28 2930 31

39 4041 42

53 5456

5524 63

Geographical locationof the stations

Sea ofMarmara

Figure 2. Spatial distribution of Turkey’s geographical regions and location of 70 stations with numbers used in the study (BLS:Black Sea; MAR: Marmara; AEG: Aegean; MED: Mediterranean; SAN: Southeastern Anatolia; CAN: Central Anatolia; EAN: Eastern

Anatolia) (see Table III for names of the stations)

Table I. Populations (de facto) and annual rates of change of Turkey’s geographical regions(DIE, 1997)

Region Census population Annual rate of

1990 1997change (1990–1997) (‰)

Black Sea 8 136 984 7 843 966 −5.16Marmara 13 295 607 16 186 673 27.67Aegean 7 594 977 8 452 087 15.04Mediterranean 7 026 489 8 058 311 19.27Southeastern Anatolia 5 159 464 6 128 973 24.31Central Anatolia 9 913 306 10 580 657 9.16Eastern Anatolia 5 346 208 5 614 907 6.90

Total (Turkey) 56 473 035 62 865 574 15.08

1990–97 period (Table I). The greatest change occurred in the Marmara region, with a rate of 27.67%; thelowest was in the Black Sea region with a rate of −5.16%.

Karl et al. (1988) classified US cities in their study. If the station classification used by Karl et al. (1988)is considered, almost all stations we have selected for the study are located in medium urban and large urbancities. We have slightly modified their original categories by considering city sizes, urban–rural characteristicsand growth tendencies in Turkey. Our modification divides the ‘medium urban category’ into two classes(Table II). Based on these considerations, the classification of Turkish stations and the number of stationswithin these classes are given in Table II. Of the 70 stations, one station is small urban (rural–suburban), nineare medium urban (suburban), and 19 and 41 are respectively medium and large urban stations characterizedby a high rate of population increase (Table III). The large urban stations constitute about 59% of the total,which is the same based on both classifications. Most of the stations are very likely to have been affectedby rapid urbanization, and thus subject to both urban heat island effects and urban cooling effects. Boththe urban warming and the urban cooling, due to the heat island effect and the effect of air pollutants (e.g.

Table II. Classification of Turkish stations for the study

Population size Classification Station number

Class symbol Urbanization characteristic(percentage)

P < 2000 S1-I Rural (true rural) 0 (0)2000 ≤ P < 10 000 S1-II Small urban (rural–suburban) 1 (1.43)10 000 ≤ P < 50 000 S2-I Medium urban (suburban) 9 (12.86)50 000 ≤ P < 10 0000 S2-II Medium urban (urban) 19 (27.14)P ≥ 100 000 S3 Large urban (urban) 41 (58.57)

Table III. Population of provinces and districts where stations we used are located in the census years of 1990 and 1997,and annual rate of change during the period from 1990 to 1997. Arranged by using the original figures from DIE (1997)

Region Station Latitude (N) Population of City Centre (de facto) Classification

No Namelongitude (E)

1990 1997 Annual rate ofchange (‰)

of cities

BLS 1 Hopa 41°24′, 41°26′ 11 507 14 287 30.44 S2-I2 Rize 41°02′, 40°31′ 52 031 73 994 49.53 S2-II3 Trabzon 41°00′, 39°43′ 146 714 182 552 30.74 S34 Giresun 40°55′, 38°23′ 67 604 74 146 12.99 S2-II5 Samsun 41°17′, 36°18′ 303 356 338 387 15.37 S36 Sinop 42°01′, 35°10′ 25 537 28 257 14.24 S2-I7 Inebolu 41°59′, 33°47′ 8 350 8 974 10.14 S1-II8 Kastamonu 41°22′, 33°47′ 51 560 59 145 19.30 S2-II9 Merzifon 40°52′, 35°28′ 40 431 42 230 8.12 S2-I

10 Corum 40°33′, 34°57′ 116 810 147 112 32.44 S311 Zonguldak 41°27′, 31°48′ 117 975 106 176 -14.82 S312 Bolu 40°44′, 31°36′ 61 509 80 225 37.37 S2-II

MAR 13 Adapazarı 40°47′, 30°25′ 169 091 183 265 11.32 S314 Izmit 40°46′, 29°56′ 190 741 198 200 5.40 S315 Goztepe (Istanbul) 40°58′, 29°05′ 6 629 431 8 566 823 36.06 S316 Sarıyer 41°08′, 29°04′ 160 075 214 377 41.08 S317 Florya (Istanbul) 40°59′, 28°48′ 6 629 431 8 566 823 36.06 S318 Luleburgaz 41°24′, 27°21′ 52 384 72 693 48.08 S2-II19 Edirne 41°40′, 26°34′ 102 345 115 083 16.50 S320 Tekirdag 40°59′, 27°33′ 80 442 100 557 31.39 S321 Bilecik 40°09′, 29°58′ 23 273 31 140 40.96 S2-I22 Bursa 40°11′, 29°06′ 834 576 1 160 395 46.36 S323 Canakkale 40°08′, 26°24′ 53 995 69 373 35.25 S2-II24 Biga 40°13′, 27°15′ 20 753 25 698 30.08 S2-I25 Bandırma 40°21′, 27°58′ 77 444 90 221 21.48 S2-II26 Balıkesir 39°39′, 27°52′ 170 589 189 987 15.15 S3

AEG 27 Kutahya 39°25′, 29°58′ 130 944 162 319 30.21 S328 Usak 38°41′, 29°24′ 105 270 124 356 23.44 S329 Afyon 38°45′, 30°32′ 95 643 113 510 24.09 S330 Dikili 39°03′, 26°52′ 10 023 11 583 20.35 S2-I31 Akhisar 38°55′, 27°51′ 73 944 80 653 12.22 S2-II

(continued overleaf )

Table III. (Continued )

Region Station Latitude (N) Population of City Centre (de facto) Classification

No Namelongitude (E)

1990 1997 Annual rate ofchange (‰)

of cities

32 Manisa 38°37′, 27°27′ 158 928 201 340 33.27 S333 Izmir 38°26′, 27°10′ 1 757 414 2 117 811 26.24 S334 Aydın 37°51′, 27°50′ 107 011 133 757 31.38 S335 Mugla 37°13′, 28°22′ 35 605 40 586 18.41 S2-I36 Bodrum 37°02′, 27°26′ 20 931 24 385 21.48 S2-I

MED 37 Burdur 37°40′, 30°20′ 56 432 60 693 10.24 S2-II38 Isparta 37°45′, 30°33′ 112 117 134 271 25.36 S339 Alanya 36°33′, 32°00′ 52 460 117 311 113.20 S340 Silifke 36°23′, 33°56′ 46 858 83 390 81.07 S2-II41 Mersin 36°48′, 34°38′ 422 357 501 398 24.13 S342 Adana 36°59′, 35°21′ 916 150 1 185 049 36.20 S343 Iskenderun 36°35′, 36°10′ 154 807 161 728 8.15 S344 Antakya 36°12′, 36°10′ 128 871 139 046 16.25 S345 Kahramanmaras 37°36′, 36°56′ 228 129 303 594 40.20 S3

SAN 46 Gaziantep 37°05′, 37°22′ 603 434 798 287 39.36 S347 Adıyaman 37°45′, 38°17′ 100 045 212 475 105.94 S348 Sanlıurfa 37°08′, 38°46′ 276 528 410 762 55.66 S349 Diyarbakır 37°53′, 40°12′ 373 810 511 640 44.15 S350 Mardin 37°18′, 40°44′ 53 005 61 529 20.97 S2-II51 Siirt 37°55′, 41°57′ 68 320 107 067 63.19 S352 Cizre 37°19′, 42°11′ 50 023 63 344 33.21 S2-II

CAN 53 Yozgat 39°49′, 34°48′ 50 335 59 466 23.45 S2-II54 Sivas 39°45′, 37°01′ 223 115 232 352 5.71 S355 Cankırı 40°36′, 33°37′ 45 496 54 311 24.91 S2-II56 Ankara 39°57′, 32°53′ 2 584 594 3 085 078 24.90 S357 Eskisehir 39°46′, 30°31′ 413 082 454 536 13.45 S358 Kırsehir 39°08′, 34°10′ 73 538 76 917 6.32 S2-II59 Kayseri 38°45′, 35°29′ 425 776 568 376 40.63 S360 Nigde 37°58′, 34°41′ 55 035 68 746 31.29 S2-II61 Konya 37°58′, 32°33′ 513 346 702 842 44.19 S3

EAN 62 Kars 40°37′, 43°06′ 78 455 93 038 23.98 S2-II63 Igdır 39°55′, 44°03′ 35 858 45 941 34.85 S2-I64 Agrı 39°44′, 43°03′ 58 038 69 384 25.12 S2-II65 Erzurum 39°57′, 41°10′ 242 391 298 735 29.40 S366 Erzincan 39°45, 39°30′ 91 772 102 304 15.28 S367 Malatya 38°21′, 38°19′ 273 268 400 248 53.68 S368 Elazıg 38°39′, 39°15′ 204 603 250 534 28.49 S369 Van 38°27′, 43°19′ 153 111 226 965 55.37 S370 Hakkari 37°34′, 43°46′ 30 407 57 077 88.57 S2-II

sulphur dioxide (SO2) and particulate matter, aerosols, etc.) respectively, may have had a positive and negativeradiative forcing on the nature and magnitude of the year-to-year variations and the secular trends. An urbancooling effect would show up particularly in daytime (i.e. maximum) temperatures of some stations with lowurban air quality.

In Turkey, almost all principal and even ordinary climatological stations have been surrounded by therapidly urbanizing areas of cities since the mid to late 1970s. Urban development in developing countries is

quite different compared with the developed countries. The high rates of population increase in those countriesand mass human migrations towards medium size (i.e. districts, towns) and large cities and metropolitan areashave caused large disorganized legal and illegal settlements in the old cities or newly urbanizing cities. Thissituation in Turkey has led the city centres and their surrounding urban and suburban areas to grow in a veryfast and unplanned manner. These adverse effects of rapid and unplanned urbanization have also led to asignificant change in vegetation and other surface land characteristics of the urbanized and/or urbanizing areasof Turkey. Consequently, meteorological observation sites have been affected by changes in surface features,particularly by decreases (increases) in the existing and/or being planted vegetation cover in nearby areas.Man-made buildings, asphalt-covered and dark-coloured streets, and other types of infrastructure activity andservices have also affected the weather stations. In some cases, newly planted trees, green belts, parks, etc.near the station can affect the observed values, and thus the natural variations and trends. A large numberof studies (Oke, 1973, 1979, 1982; Landsberg, 1981; Kukla et al., 1986; Karl et al., 1988; Karl and Jones,1989; Jones et al., 1990; etc) addressed the issues of urbanization detection (urban growth and populationincrease) and urbanization or heat island effect on the urban temperature regime, and long-term temperaturevariations and trends. Tayanc et al. (1997) examined the effects of urbanization on the Turkish temperaturesand the relationship between air pollution and temperature trends and variations in detail.

4. METHODOLOGY

The non-parametric M–K rank correlation test (Sneyers, 1990) was used to detect any possible trend intemperature series, and to test whether or not such trends are statistically significant. A detailed assessmentfor testing of climatic data unevenly distributed in time and a comparison of methods for estimating thesignificance level of a trend can be found in a recent study performed by Huth (1999). The M–K test statisticu(t) is a value that indicates direction (or sign) and statistical magnitude of the trend in a series. When thevalue of u(t) is significant at the 5% significance level, it can be decided whether it is an increasing or adecreasing trend depending on whether u(t) > 0 or u(t) < 0. A 1% level of significance was also taken intoconsideration. Partial and short-period trends, and a change point or beginning point of a trend in climaticseries were investigated by using time-series plot of the u(ti) and u′(ti) values. In order to obtain such a time-series plot, sequential values of the statistics u(t) and u′(t) were computed from the progressive analysis ofthe M–K test. Following Sneyers (1990), this procedure is formulated as follows: first, original observationsare replaced by their corresponding ranks yi , which are arranged in ascending order. Then, for each term yi ,the number nk of terms yj preceding it (i > j ) is calculated with (yi > yj ), and the test statistic ti is written as

ti =i∑

The distribution function of the test statistic ti has a mean and a variance derived by

E(ti) = i(i − 1)/4 and var(ti) = [i(i − 1)(2i + 5)]/72

Values of the statistic u(ti) are then computed as

u(ti) = [ti − E(ti)]/√

var(ti)

Finally, the values of u′(ti ) are similarly computed backward, starting from the end of the series. With atrend, intersection of these curves enables the beginning of a trend in the series to be located approximately.Without any trend, a time-series plot of the values u(ti) and u′(ti) shows curves that overlap several times.An 11-point Binomial filter was used as a low-pass filter to investigate visually the characteristics of thelong-period fluctuations in the series (WMO, 1966).

The non-parametric W–W serial correlation test was chosen to determine randomness against the serialdependence (persistence) in temperature series (Sneyers, 1990). Sneyers (1992) advised use of the W–Wserial correlation test combined with the M–K and Spearman rank correlation tests, because changes inclimatic series seem, generally, to proceed in an abrupt manner rather than a linear or monotonic trend. TheW–W statistic u(r) gives objective information about the nature and magnitude of possible persistence ina long time-series. Using a one-sided test of the normal distribution, the null hypothesis of randomness isrejected for large values of the test statistic u(r). The alternatives to randomness may indicate the presence ofsome forms of fluctuation or of abrupt change. In most cases, for annual and winter precipitation series andsummer maximum temperatures for Turkey, a significant positive serial correlation (PSC) coefficient revealsthe existence of a low-frequency fluctuation (Turkes et al., 1996; Turkes, 1998).

The least-squares linear regression equations were calculated to detect warming (cooling) rates per decade.In estimating linear regression lines, we have used the simple least-squares approach with time as theindependent variable, and temperature values as the dependent variable. The statistical significance of eachestimated X (β) coefficient was tested using the Student’s t test for significance with (n − 2) degrees offreedom. In using two-tailed test of the Student’s t distribution, the null hypothesis for the absence of anytrend is rejected for large values of |t |. Programs for all computations and statistical analyses were preparedusing the FORTRAN programming language.

The interpolation method of kriging was used in order to produce the contours shown on the spatialdistribution maps. It has been applied to the resultant test statistics u(t) of temperature trends from the M–Ktest by means of a mapping package. Nevertheless, the trend analysis results were not assessed for fieldsignificance.

5. RESULTS OF ANALYSES

Only a summary table (Table IV) has been given in this section for the results of the M–K rank correlationand the W–W serial correlation tests, owing to the large volume of results, although the tables have beenarranged for all the resultant test statistics.

5.1. Trends and changes in temperature series

5.1.1. Trends and changes in annual temperature series. For annual mean temperatures, the year-to-yearvariations in the series are generally characterized by a PSC coefficient from the W–W test. For annual meantemperatures series, this is an indicator of low-frequency fluctuation of various types and levels, but not anabrupt change. The spatial distribution pattern is not complex, even though the resultant test statistics ofthe M–K test give both negative and positive trends. Trends are not significant in most stations, except forwarming in a few stations (Table IV). Significant positive trends are evident over the eastern MED sub-region,which is one of the highly urbanized areas of Turkey, namely the Adana–Mersin district (Figure 3(a)).

For annual maximum temperatures, significant PSC coefficients characterize the observed low-frequencyfluctuations in the series. As with annual mean temperatures, these series show mostly statistically insignificantincreasing and decreasing trends over much of Turkey. The slightly increasing trends show up over the westernand eastern regions of the country, in which the significant warming is seen over the inner part of the Aegeanregion and in some small areas of the SAN region (Figure 3(b)). Decreasing trends are observed mainly overthe CAN region, with a small area of significant cooling within that region, and the eastern BLS sub-region.

For annual minimum temperatures, the year-to-year variations of 40 stations are characterized by asignificant PSC coefficient (Table IV). Minimum temperatures have tended to increase significantly at 31of the 70 stations in Turkey (Table IV). Minimum temperatures show a well-defined spatial coherencecharacterized by a significant strong warming (Figure 3(c)), the probability of which is very much belowthe 0.01 significance level at 24 stations. Stronger warming trends of annual minimum temperatures aremostly observed in the stations that are rapidly urbanizing or which are already urbanized cities, as in springand summer. The spatial distribution pattern of significant warming trends exhibits an apparent geographical

Table IV. Number of the stations indicating a significant trend and/or a serial correlation in the mean, maximum andminimum temperature series of 70 stations, at the 0.05 level of significance, according to the Mann-Kendall (M–K) and

Wald-Wolfowitz (W–W) testsa

Region Winter Spring Summer Autumn Annual

M–K W–W M–K W–W M–K W–W M–K W–W M–K W–W+ − + − + − + − + − + − + − + − + − + −

Mean temperaturesBLS 1 2 1 5 6 1 1MAR 2 2 5 1 1AEG 1 2 8 2MED 1 2 1 1 9 3 2 3 3SAN 1 2 3 1 2CAN 1 1 3 3 1 1EAN 1 3 2 2 4

Total 2 8 12 36 13 8 9 9

Maximum temperaturesBLS 2 1 2 1 6 3 1 1 4MAR 1 1 7 1 1 2AEG 1 1 2 9 3 3MED 1 5 1 1 1 3SAN 1 1 2 2 5 3 2CAN 1 2 6 1 4 1 2EAN 1 2 1 4 1 3 1 5

Total 5 3 4 14 42 6 10 11 21

Minimum temperaturesBLS 1 2 4 3 3 9 1 5 1 2 1 8MAR 5 2 6 1 12 1 2 5 1 8AEG 6 3 8 9 4 6 4MED 3 3 5 5 6 9 3 1 3 6 6SAN 4 2 2 5 3 1 4 5CAN 3 4 3 6 2 3 4EAN 1 1 3 1 5 2 8 2 2 3 1 5 1 5

Total 7 4 30 20 36 58 26 9 34 40

a +: increasing trend from the M–K test and PSC coefficient from the W–W test; −: decreasing trend from the M–K test and negativeserial correlation coefficient from the W–W test.

autocorrelation (relation) over Turkey. This spatial pattern is described by the observed maximum warmingareas over the western parts of the MAR, BLS and CAN regions, Izmir–Manisa district of the AEG region,and eastern EAN, MED and SAN regions. On the other hand, decreasing trends that are mostly insignificantshow an apparent spatial coherence over the northern parts of the CAN and EAN regions and eastern BLSsub-region (Figure 3(c)). Erzurum station, which is in that coherent area, has a jump in the minimum seriestowards cooler temperatures.

The beginning of the secular trends and the periods of significant warming (cooling) are determined bymeans of the time-series plots of the u(t) and u′(t) values from the sequential analysis of the M–K test(Figure 4). Results from evaluation of these time-series plots are summarized for the selected stations thatare representative for the coherent regions with significant trends as follows:

• A common observed and statistically significant secular warming trend in many stations, with differentsignificant warming periods, such as in the late 1980s to 1999 at the Goztepe station, in 1970–99 at Bolu,in the late 1960s to 1999 at Izmir, in 1980–99 and the mid-1960s to 1999 at some stations.

B L A C K S E A

M E D I T E R R A N E A N S E A

a. Annualmean temperature trend

(u(t))

Sea ofMarmara

b. Annualmaximum temperature trend

(u(t))

c. Annualmaximum temperature trend

(u(t))

Sea ofMarmara

Figure 3. Spatial distribution patterns of annual mean (a), maximum (b) and minimum (c) temperature trends of 70 stations in Turkeyfrom the M–K test statistic u(t). Pale shading: significant at the 0.05 significance level; dark shading: significant at the 0.01 level.

Critical values of |1.96| and |2.58| are taken as |2.0| and |2.6| respectively in drawing contours of significance limits

• A common observed and statistically significant secular warming trend and a recent significant warmingperiod at the end of the series at Giresun, Ankara, Kırsehir, Van, Gaziantep and Mersin.

5.1.2. Trends and changes in winter temperature series. For winter mean temperatures, the results of theW–W test show they are all statistically random against the serial dependence. Both weak negative andpositive trends characterize the winter mean temperature series (Figure 5(a)). Slightly decreasing trends areevident over the western and eastern BLS region, whereas slightly increasing trends are found over the

Zonguldak annual minimum (BLS)

−3−2−101234

1930 1940 1950 1960 1970 1980 1990 2000Year

Giresun annual minimum (BLS)

−4−3−2−101234

1930 1940 1950 1960 1970 1980 1990 2000

Göztepe annual minimum (MAR)

−4−3−2−1012345

1930 1940 1950 1960 1970 1980 1990 2000Year

Bolu annual minimum (BLS)

−4−3−2−10123456

1930 1940 1950 1960 1970 1980 1990 2000Year

Erzurum annual minimum (EAN)

−5−4−3−2−101234

1930 1940 1950 1960 1970 1980 1990 2000

Ankara annual minimum (CAN)

−3−2−101234

1930 1940 1950 1960 1970 1980 1990 2000

Kirsehir annual minimum (CAN)

−3−2−101234

1930 1940 1950 1960 1970 1980 1990 2000

Van annual minimum (EAN)

−4−3−2−10123456

1930 1940 1950 1960 1970 1980 1990 2000

Usak annual minimum (AEG)

−3−2−10123

1930 1940 1950 1960 1970 1980 1990 2000Year

Ízmir annual minimum (AEG)

−4−3−2−1012345

1930 1940 1950 1960 1970 1980 1990 2000

Gaziantep annual minimum (SAN)

−4−3−2−1012345

1930 1940 1950 1960 1970 1980 1990 2000

Sanliurfa annual minimum (SAN)

−4−3−2−1012345

1930 1940 1950 1960 1970 1980 1990 2000

Mersin annual minimum (MED)

−5−4−3−2−101234567

1930 1940 1950 1960 1970 1980 1990 2000

Adana annual minimum (MED)

−4−3−2−101234567

1930 1940 1950 1960 1970 1980 1990 2000Year

−3−2−10123

1930 1940 1950 1960 1970 1980 1990 2000Year

Elazig annual minimum (EAN)

Figure 4. Temporal patterns of the trends in annual minimum temperature series of selected stations in Turkey from sequential valuesof the statistics u(t) ( ) and u′(t) (–ž–) of the M–K test, with critical value of ±1.96 at the 0.05 level of significance (- - - - )

mid-western and eastern parts of the CAN and western part of the SAN along with the Mersin–Adanadistrict.

For winter maximum temperatures, most winter maximum series are characterized by a negative serialcorrelation coefficient that is mostly insignificant. Even though negative coefficients are not statisticallysignificant, high-frequency oscillations are apparent in the series (Figure 6). Spatial and temporal patterns oftrends in maximum temperatures are very similar to those of mean temperatures. Trends in most series are notsignificant (Table IV and Figure 5(b)). A general cooling is dominant over the BLS region and mid-southernparts of the CAN region, whereas a general warming is seen over the western and mid-eastern regions ofTurkey. A few of the increasing trends are significant.

For winter minimum temperatures, the majority of the series are random against the PSC. A significantPSC coefficient is found only for a few stations located on the Mediterranean coast of the Anatolian Plateau.Winter minimum temperatures show a general increasing trend over much of Turkey, except for some areasparticularly in the BLS region (Figure 5(c)). A coherent region generally characterized by a significantwarming is evident at the well-known urbanized stations with a high rate of population increase in theMED region. It is seen that some stations, such as Goztepe, Mersin and Adana, show a systematic warming

B L A C K S E A

Sea ofMarmara

a. Wintermean temperature trend

(u(t))

b. Wintermaximum temperature trend

(u(t))

c. Winterminimum temperature trend

(u(t))

Figure 5. As in Figure 3, but for winter

trend, if time-series plots of the selected stations are assessed (Figure 7). On the other hand, some stationsexhibit high year-to-year variations without showing any apparent secular trend. Minimum temperatures ofsome stations have tended to increase after 1992, which was one of the coldest years in the observationrecords for most stations in Turkey (Turkes, 1995; Turkes et al., 1995). Nevertheless, this warming has notreached the significance level on time-series plots of the u(t) and u′(t) values (Figure 7).

5.1.3. Trends and changes in spring temperature series. For spring mean temperatures, most series arecharacterized by an insignificant negative serial correlation coefficient. Most of the country, except the CAN

Giresun winter maximum (BLS)

1930 1940 1950 1960 1970 1980 1990 2000Year

Mersin winter maximum (MED)

1930 1940 1950 1960 1970 1980 1990 2000Year

Sanliurfa winter maximum (SAN)

1930 1940 1950 1960 1970 1980 1990 2000

Erzurum winter maximum (EAN)

-8-7-6-5-4-3-2-10123

1930 1940 1950 1960 1970 1980 1990 2000

1930 1940 1950 1960 1970 1980 1990 2000Year

Göztepe winter maximum (MAR)

Adana winter maximum (MED)

12131415

16171819

1930 1940 1950 1960 1970 1980 1990 2000Year

Ankara winter maximum (CAN)

1930 1940 1950 1960 1970 1980 1990 2000

1930 1940 1950 1960 1970 1980 1990 2000Year

Zonguldak winter maximum (BLS)

1011121314

1930 1940 1950 1960 1970 1980 1990 2000Year

Usak winter maximum (AEG)

Gaziantep winter maximum (SAN)

101112

1930 1940 1950 1960 1970 1980 1990 2000Year

Kirsehir winter maximum (CAN)

0123456789

1930 1940 1950 1960 1970 1980 1990 2000

Van winter maximum (EAN)

1930 1940 1950 1960 1970 1980 1990 2000

1930 1940 1950 1960 1970 1980 1990 2000Year

Bolu winter maximum (BLS)

Elazig winter maximum (EAN)

1930 1940 1950 1960 1970 1980 1990 2000Year

Ízmir winter maximum (AEG)

Figure 6. Interannual variations in winter maximum temperature series of selected stations in Turkey, with smoothed line by the Binomialfilter ( ) with padded ends and long-term average (- - - - )

region, experiences either weak or strong warming (Figure 8(a)). Warming trends are significant only at eightstations (Table IV).

For spring maximum temperatures, insignificant negative serial correlation coefficients describe the highyear-to-year variations in the series. Spring maximum temperatures do not show apparent spatial distributionpatterns characterized by a significant warming or a cooling. Increasing trends at a weak degree of significancelevel are seen over the BLS, northern MAR and EAN regions, along with a slight significant warming in theIzmir–Dikili district and the SAN region. Decreasing trends indicate a spatial coherence over the middle partof the CAN region (Figure 8(b)).

For spring minimum temperatures, the year-to-year variations are described mostly by a PSC coefficient, 20of which are statistically significant (Table IV). A considerable number of these significant PSC coefficientscoincide with the series that have tended to increase significantly in the mean of the series rather than alow-frequency fluctuation (Figure 9). Spring, as in the results from the past study by Turkes et al. (1996),has experienced not only a statistically significant but also a very rapid night-time warming over much ofTurkey. Minimum temperatures have significantly increased at 30 stations (Table IV), 22 of which are at the0.01 significance level. Coherent regions with a significant night-time warming appear mainly over the most

Giresun winter minimum (BLS)

1930 1940 1950 1960 1970 1980 1990 2000

Göztepe winter minimum (MAR)

1930 1940 1950 1960 1970 1980 1990 2000

Mersin winter minimum (MED)

-3-2-101234

1930 1940 1950 1960 1970 1980 1990 2000

Sanliurfa winter minimum (SAN)

1930 1940 1950 1960 1970 1980 1990 2000

Erzurum winter minimum (EAN)

-4-3-2-10123

1930 1940 1950 1960 1970 1980 1990 2000

Van winter minimum (EAN)

-3-2-101234

1930 1940 1950 1960 1970 1980 1990 2000

Ankara winter minimum (CAN)

1930 1940 1950 1960 1970 1980 1990 2000

Kirsehir winter minimum (CAN)

1930 1940 1950 1960 1970 1980 1990 2000

Zonguldak winter minimum (BLS)

1930 1940 1950 1960 1970 1980 1990 2000

Bolu winter minimum (BLS)

1930 1940 1950 1960 1970 1980 1990 2000

Ízmir winter minimum (AEG)

1930 1940 1950 1960 1970 1980 1990 2000

Usak winter minimum (AEG)

1930 1940 1950 1960 1970 1980 1990 2000

Adana winter minimum (MED)

1930 1940 1950 1960 1970 1980 1990 2000

Gaziantep winter minimum (SAN)

1930 1940 1950 1960 1970 1980 1990 2000

Elazig winter minimum (EAN)

Figure 7. As in Figure 4, but for winter minimum temperature series

urbanized or rapidly urbanizing cities with a high rate of population increase (Figure 8(c)). These warmingareas can be summarized as follows: Istanbul and its large surrounding urban and suburban areas (Istanbulmetropolitan area); western parts of the BLS and CAN regions; the Izmir–Manisa district; the MED regionand western part of the SAN region; a coherent area from the middle BLS region to the MED warming areavia the eastern part of the CAN region; and the eastern part of the EAN region.

Time-series of variations and trends from an 11-point Binomial low-pass filter and the u(t) and u′(t) valuesof the M–K test both prove that series of most stations, even in the different geographical regions of Turkey,have been rather similar in terms of their year-to-year variability, long-period fluctuation and secular and/orpartial trend patterns (Figures 9 and 10). This close similarity also includes the peculiarities for the beginningof the trends and periods of significant warming in some series. Temporal characteristics derived from thetime-series plots can be summarized as follows:

• At some stations, the beginning point of the trend is found in the late 1940s and early 1950s. In manyof them, the period of significant warming begins immediately after the early 1960s or in the early tomid 1970s.

a. Springmean temperature trend

(u(t))

c. Springminimum temperature trend

(u(t))

b. Springmaximum temperature trend

(u(t))

Sea ofMamara

B L A C K S E A

Figure 8. As in Figure 3, but for spring

• At some stations, the beginning point of the trend is located in the late 1950s, in 1960 and the mid to late1960s. In many of these stations, a period of significant warming begins in the late 1960s and early 1970s,and lasts to the end of the series.

• At some stations, the beginning point of the trend starts in the mid to late 1970s and early 1980s. Thesestations have a relatively shorter period of significant warming.

5.1.4. Trends and changes in summer temperature series. For summer mean temperatures, the series arecharacterized mostly by a statistically significant PSC coefficient. The PSC coefficients qualify observed low-frequency fluctuations in the series. Mean temperatures have generally shown a slight increase at many stations

Zonguldak spring minimum (BLS)

)Samsun spring minimum (BLS)

1930 1940 1950 1960 1970 1980 1990 2000

Year Year

Bolu spring minimum (BLS)

0123456

1930 1940 1950 1960 1970 1980 1990 2000

Year1930 1940 1950 1960 1970 1980 1990 2000

23456789

1011121314

Gaziantep spring minimum (SAN)

456789

1011121314

Adana spring minimum (MED)

101112131415

Afyon spring minimum (AEG)

Göztepe spring minimum (MAR)

1930 1940 1950 1960 1970 1980 1990 2000Year

1930 1940 1950 1960 1970 1980 1990 2000

Çanakkale spring minimum (MAR)

2345678

Sivas spring minimum (CAN)

-2-10123456

Ankara spring minimum (CAN)

12345678

01234567

Van spring minimum (EAN)

Giresun spring minimum (BLS)

1930 1940 1950 1960 1970 1980 1990 2000

Year1930 1940 1950 1960 1970 1980 1990 2000

Usak spring minimum (AEG)

Sanliurfa spring minimum (SAN)

Kirsehir spring minimum (CAN)

Eskisehir spring minimum (CAN)

Elazig spring minimum (EAN)

Ízmir spring minimum (AEG)

Figure 9. As in Figure 6, but for spring minimum temperature series

Zonguldak spring minimum (BLS)

-3-2-101234

Giresun spring minimum (BLS)

-3-2-101234

Göztepe spring minimum (MAR)

-3-2-1012345

Bolu spring minimum (BLS)

-3-2-1012345

-4-3-2-10123

Ankara spring minimum (CAN)

-3-2-10123

-3-2-1012345

Gaziantep spring minimum (SAN)

-3-2-101234

-3-2-1012345

Adana spring minimum (MED)

-3-2-1012345

Samsun spring minimum (BLS)

-3-2-101234

Çanakkale spring minimum (MAR)

Afyon spring minimum (AEG)

-3-2-101234

Sivas spring minimum (CAN)

-3-2-1012345

-4-3-2-1012345

Van spring minimum (EAN

1930 1940 1950 1960 1970 1980 1990 2000

Year1930 1940 1950 1960 1970 1980 1990 2000

1930 1940 1950 1960 1970 1980 1990 2000

Year1930 1940 1950 1960 1970 1980 1990 2000

1930 1940 1950 1960 1970 1980 1990 2000

Year1930 1940 1950 1960 1970 1980 1990 2000

1930 1940 1950 1960 1970 1980 1990 2000

Year1930 1940 1950 1960 1970 1980 1990 2000

1930 1940 1950 1960 1970 1980 1990 2000Year

1930 1940 1950 1960 1970 1980 1990 2000

Year1930 1940 1950 1960 1970 1980 1990 2000

Usak spring minimum (AEG)

Eskisehir spring minimum (CAN)

Sanliurfa spring minimum (SAN)

Elazig spring minimum (EAN)Kirsehir spring minimum (CAN)

Ízmir spring minimum (AEG)

Figure 10. As in Figure 4, but for spring minimum temperature series

over the western and southern regions of Turkey, along with a marked increasing trend in the MAR and SANregions and at around the Izmir–Manisa district (Figure 11(a)). These series have indicated a significantwarming trend at nine stations in different regions (Table IV). A general decreasing trend has shown up overthe rest of the country, particularly in the central and eastern regions.

a.Summermean temperature trend

(u(t))

Sea ofMamara

b.Summermaximum temperature trend

(u(t))

c.Summerminimum temperature trend

(u(t))

B L A C K S E A

Figure 11. As in Figure 3, but for summer

For summer maximum temperatures, the year-to-year variations of 42 stations are described by a statisticallysignificant PSC coefficient (Table IV). Significant PSC coefficients are a statistical indication of observedlow-frequency fluctuations in these series rather than an abrupt change (Figure 12).

Long-term variations of maximum temperature series are characterized now by both positive and negativetrends for the study period of 1929–99. Decreasing trends that are mostly insignificant show a spatialcoherence over the central parts of the MAR and CAN regions and the eastern MED sub-region (Figure 11(b)).On the other hand, summer maximum temperatures have significantly increased at nine stations (Table IV).Coherent areas with increasing trends are seen in the western and eastern regions of Turkey. Significant

Zonguldak summer maximum (BLS)

26Giresun summer maximum (BLS)

Göztepe summer maximum (MAR)

25262728293031

Bolu summer maximum (BLS)

23242526272829

Erzurum summer maximum (EAN)

Ankara summer maximum (CAN)

26272829303132

25262728293031

Van summer maximum (EAN)

24252627282930

Gaziantep summer maximum (SAN)

34353637383940

Mersin summer maximum (MED)

31Adana summer maximum (MED)

31323334353637

1930 1940 1950 1960 1970 1980 1990 2000Year

Usak summer minimum (AEG)

Sanliurfa summer minimum (SAN) Kirsehir summer maximum (CAN)

Elazig summer maximum (EAN)

Ízmir summer maximum (AEG)

Figure 12. As in Figure 6, but for summer maximum temperature series

warming trends are found in the AEG and SAN regions and northeastern part of the Anatolian Plateau(Figure 11(b)). Indeed, this present situation of increasing trends in summer maximum temperatures of somestations is considerably different from the results of our previous studies, which revealed a significant coolingat many stations in Turkey (Turkes, 1996; Turkes et al., 1996). The period of those studies was 1930–93.That period included a short but marked period of cooler than normal maximum temperature conditions inthe early to mid 1980s and ended at the single marked cooler year of 1992. These decreased temperatureconditions controlled the direction of the trend at most stations towards cooling. However, it is seen in thepresent study that marked increases in maximum temperatures of many stations after 1992 have controlledthe direction, or nature (sign), of the trend (Figure 12). Consequently, it is found that an increasing trend hasstarted to dominate at some stations. As we have already pointed out, this explanation is valid for annualmean and maximum temperature series compared with the previous results for 1930–93.

For summer minimum temperatures, concerning the non-randomness characteristics of climatic series, thisseries is the most striking temperature series in Turkey. Minimum temperature series are not random eitheragainst the persistence or against the secular trend. Year-to-year variations of most series are characterizedby a significant PSC coefficient, as in the mean and maximum temperatures. Of the 70 stations, 58 have asignificant PSC coefficient (Table IV).

The spatial pattern of secular trends in summer minimum temperature series is considerably similar to thepattern of annual minimum temperature trends regarding both nature and magnitude. Minimum temperatureshave tended to increase at the majority of stations in Turkey, most of which are located in the cities thatare already urbanized or rapidly urbanizing. Increasing trends show a large spatial coherence over much ofTurkey and are significant at 33 stations (Table IV), 30 of which are at the 0.01 level. Coherent areas withsignificant warming trends appear over the following regions (Figure 11(c)): the Istanbul–Kocaeli Plateau;the western BLS sub-region; the Aegean region; most of the CAN region, along with an area extending tothe middle BLS sub-region; the MED region, western part of the SAN region, and eastern part of the EANregion. Decreasing trends are evident over the Thrace (Trakya in Turkish) sub-region of the MAR region andwestern part of the EAN region (Figure 11(c)). Nevertheless, decreasing trends are significant only at oneand two stations of these regions respectively.

Apart from the secular trends that are clearly seen in time-series plots of the M–K u(t) and u′(t) values,periods of significant warming occur during the years between about the mid 1980s and 1999 at many stations,for instance at Bolu, Goztepe, Usak, Izmir, Sanlıurfa, etc. (Figure 13). A shorter period of significant warmingalso shows up at many stations during recent years.

5.1.5. Trends and changes in autumn temperature series. For autumn mean temperatures, the year-to-yearvariations of most series are random against the serial dependence. Mean temperatures have significantlydecreased only at ten stations (Table IV), although decreasing trends show a large spatial coherence overTurkey (Figure 14(a)). Significant cooling trends are evident over the middle and eastern sub-regions of theBLS region, and middle part of the EAN region that connects with cooling area on the eastern BLS coast.The beginning points of the secular decreasing trends are located approximately in the mid 1950s, mid to late1960s, early to mid 1970s and 1980s at many stations (Figure 15). Increasing trends are evident only on theMED coast, with significant trends at three stations.

For autumn maximum temperatures, most series are regarded as random with respect to the persistence,because year-to-year variations of these series are characterized by an insignificant positive or negative serialcorrelation coefficient. Most series are also random against any significant trend. Maximum temperatureshave tended to decrease slightly in the MAR, BLS and CAN regions and the southeastern corner of the EANregion (Figure 14(b)). Decreasing trends are significant only at six stations (Table IV). A weak increasingtrend is apparent in the AEG and SAN regions.

For autumn minimum temperatures, the year-to-year variations in the series are characterized by a significantPSC coefficient at some stations and by a significant negative serial correlation coefficient at a few stations(Table IV). Some of these series show low-frequency fluctuations and rapid increasing trends, and some arecharacterized by an abrupt change. The minimum temperature series have shown a significant warming trendat 16 stations, most of which are located in the AEG, MED and SAN regions, along with a few stationsin the CAN and EAN regions (Figures 14(c) and 16). Decreasing trends are evident at the stations over theMAR, BLS and EAN regions. Ten of the decreasing trends are significant. Significant cooling trends appearover the Trakya and eastern BLS sub-regions and the middle and northern parts of the EAN region.

5.2. Trend rates in temperature series

As in Turkes et al. (1996), the nature and magnitude of the least-squares linear regression lines coincideperfectly with the results of the M–K test at most stations. Spatial distribution patterns of linear trends alsolook like the non-linear trends. Significant and/or striking results have been summarized for linear trends andlinear trend rates per decade in this section.

Zonguldak summer minimum (BLS)

-3-2-101234

1930 1940 1950 1960 1970 1980 1990 2000

Giresun summer minimum (BLS)

-4-3-2-10123456

1930 1940 1950 1960 1970 1980 1990 2000

Göztepe summer minimum (MAR)

-3-2-10123456

1930 1940 1950 1960 1970 1980 1990 2000

Bolu summer minimum (BLS)

-3-2-10123456

1930 1940 1950 1960 1970 1980 1990 2000

Erzurum summer minimum (EAN)

-5-4-3-2-10123

1930 1940 1950 1960 1970 1980 1990 2000

-4-3-2-10123

1930 1940 1950 1960 1970 1980 1990 2000

Ankara summer minimum (CAN)

-3-2-1012345

1930 1940 1950 1960 1970 1980 1990 2000

-3-2-101234

1930 1940 1950 1960 1970 1980 1990 2000

-4-3-2-1012345

1930 1940 1950 1960 1970 1980 1990 2000

Ízmir summer minimum (AEG)

-3-2-101234567

1930 1940 1950 1960 1970 1980 1990 2000

Gaziantep summer minimum (SAN)

-3-2-1012345

1930 1940 1950 1960 1970 1980 1990 2000

-3-2-1012345

1930 1940 1950 1960 1970 1980 1990 2000

Mersin summer minimum (MED)

-4-3-2-1012345678

1930 1940 1950 1960 1970 1980 1990 2000

Adana summer minimum (MED)

-3-2-1012345678

1930 1940 1950 1960 1970 1980 1990 2000

Van summer minimum (EAN)

-3-2-101234567

Usak summer minimum (AEG)

Kirs ehir summer minimum (CAN)Sanliurfa summer minimum (SAN)

Elazig summer minimum (EAN)

Figure 13. As in Figure 4, but for summer minimum temperature series

5.2.1. Trend rates in mean temperature series. For annual mean temperatures, the series for Turkey haverevealed a significant linear increasing trend at ten stations and a decreasing trend at three stations. Increasingtrends are apparent in the MAR, AEG, MED, SAN and EAN regions of Turkey, whereas cooling trends areevident in the BLS and CAN regions (Figure 17(a)). The highest warming, which is significant at the 0.01level, is seen at the Cizre station (SAN) with a trend rate of 0.34 °C per decade. Other highest significantlinear warming rates per decade for the geographical regions are as follows: 0.09 °C at Florya (MAR); 0.08 °Cat Usak and Izmir (AEG); 0.19 °C at Alanya (MED); 0.14 °C at Gaziantep (SAN); 0.12 °C at Sivas (CAN).A trend rate of −0.18 °C per decade for the Inebolu station (BLS) is significant at the 0.01 level.

For winter mean temperatures, the trend rates of the series are mostly weak and insignificant (Figure 18(a)).Apparent cooling trends are found at Hopa and Inebolu (BLS), with rates of 0.48 °C and 0.41 °C perdecade respectively. The highest warming is seen at Kars (EAN), with a trend rate of 0.36 °C perdecade.

Sea ofMarmara

c. Autumnminimum temperature trend

(u(t))

b. Autumnmaximum temperature trend

(u(t))

a. Autumnmean temperature trend

(u(t))

B L A C K S E A

Figure 14. As in Figure 3, but for autumn

For spring mean temperatures, the series have shown mostly positive trends (Figure 18(a)). Linearincreasing trends are significant at eight stations, five of which are found in the MED and SAN regions.Significant warming trend rates per decade vary from 0.12 to 0.49 °C, the latter of which is the highestwarming trend rate for Cizre (SAN).

Summer mean temperatures have tended to increase at most stations (Figure 18(a)). Linear increasing trendsat nine stations are significant. Significant warming trends at the 0.01 level are found at stations in the AEG,MED and SAN regions. Significant warming trend rates per decade vary between 0.11 and 0.39 °C (the highestat Cizre again). Summer mean temperatures have also decreased significantly at three stations.

Samsun autumn mean (BLS)

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Çorum autumn mean (BLS)

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Afyon autumn mean (AEG)

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Igdir autumn mean (EAN) Elazig autumn mean (EAN)

Figure 15. As in Figure 4, but for autumn mean temperature series

For autumn mean temperatures, the series have indicated a decreasing trend over most of Turkey, except forthe MED region (Figure 18(a)). Linear decreasing trends are significant at 12 stations. Significant decreasingtrends dominate particularly in the BLS region, with a total number of seven stations. Significant cooling inthe BLS region varies between trend rates of −0.13 and −0.27 °C per decade. The largest cooling is found atHopa (BLS), with a trend rate of −0.27 °C per decade. Mean temperature series have also shown a warmingat the Alanya, Mersin and Adana stations in the coastal zone of the MED region.

5.2.2. Trend rates in maximum temperature series. For annual maximum temperatures, the series for Turkeyare characterized mostly by increasing trends, except for those stations in the BLS and CAN regions(Figure 17(b)). Significant linear increasing trends are found at 11 stations and show a spatial coherence overthe AEG and SAN regions. The highest daytime warming, which is significant at the 0.01 level, is at Kars(EAN), with a trend rate of 0.33 °C per decade. Other highest warming rates per decade, whether significantor not, are found at the following stations: 0.16 °C at Luleburgaz (MAR); 0.12 °C at Dikili (AEG); 0.11 °Cat Antakya (MED); 0.31 °C at Adıyaman (SAN); 0.12 °C at Malatya (EAN). On the other hand, maximum

Samsun autumn minimum (BLS)

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Sanliurfa autumn minimum (SAN)

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Adana autumn minimum (MED)

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Rize autumn minimum (BLS)

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Mersin autumn minimum (MED)

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Elazig autumn minimum (EAN)

Figure 16. As in Figure 4, but for autumn minimum temperature series

temperatures have revealed a significant linear decreasing trend at four stations. The largest cooling exists atHopa (BLS), with a trend rate of −0.24 °C per decade.

Winter maximum temperatures have tended to increase slightly at most of the stations (Figure 18(b)). Onlytwo stations have a significant linear warming trend. The highest daytime warming is at Kars (EAN), with a0.49 °C trend rate per decade. Some other highest warming rates per decade for the regions, whether significantor not, are as follows: 0.07 °C at Bolu (BLS); 0.17 °C at Edirne (MAR); 0.18 °C at Usak (AEG); 0.15 °C atAntakya (MED); 0.32 °C at Adıyaman (SAN); 0.14 °C at Sivas (CAN); 0.28 °C at Malatya (EAN). Thereare two stations in the BLS region characterized by a significant linear cooling trend. The largest significantdaytime cooling is seen at Hopa (BLS), with a −0.56 °C trend rate per decade.

For spring maximum temperatures, the series have indicated a warming in all geographical regions exceptthe CAN region (Figure 18(b)). However, only results for four stations are significant. The highest significantdaytime warming is found at Gaziantep (SAN), with a trend rate of 0.24 °C per decade. Considerable butinsignificant linear cooling trend rates exist at Hopa (BLS) and Hakkari (EAN), with −0.21 °C and −0.23 °Cper year respectively.

Summer maximum temperatures have increased at many stations and decreased at some stations(Figure 18(b)). A large coherent area with a linear increasing trend is seen particularly over the AEG, MEDand SAN regions. Linear increasing trends are statistically significant at eight stations. On the other hand,

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a) Annual mean temperature

BLS MAR AEG MED SAN CAN EAN

b) Annual maximum temperature

c) Annual minimum temperature

Figure 17. Trend rates ( °C) per decade in annual mean (a), maximum (b), and minimum (c) temperature series of 70 stations from theleast-squares linear regression approach, in accordance with the regional order and station numbers used in the study. Black bars show

significant trend rates at the 0.05 level

decreasing trends are observed in the inner part of the BLS region, and over the MAR and CAN regions.Significant linear decreasing trends exist at six stations, three of which are located in the CAN region. Thehighest significant daytime warming is at Kars (EAN), with a trend rate of 0.48 °C per decade at the 0.01 level.The other highest significant trend rates per decade for the geographical regions, mostly at the 0.01 level, arefound at the following stations: 0.19 °C at Inebolu (BLS); 0.19 °C at Luleburgaz (MAR); 0.18 °C at Akhisar(AEG); 0.45 °C at Adıyaman (SAN); and 0.15 °C at Erzurum (EAN). The largest significant cooling trend isseen at the stations of Iskenderun (MED) and Van (EAN), with a rate of −0.19 °C per decade. Significantcooling trends in the CAN region vary between rates of −0.11 °C and −0.18 °C per decade.

Autumn maximum temperatures have tended to show a decreasing trend at most stations, especially thosein the BLS, MAR and CAN regions (Figure 18(b)). However, only five of the linear decreasing trends arestatistically significant. A −0.31 °C trend rate per decade at Hopa (BLS) is the largest daytime cooling amongthe stations. Some other marked cooling rates per decade, whether significant or not, are as follows: −0.21 °Cat Kastamonu (BLS); −0.22 °C at Bandırma (MAR); −0.13 °C at Afyon (AEG); −0.19 °C at Silifke (MED);−0.07 °C at Diyarbakır (SAN); −0.18 °C at Kırsehir (CAN); and −0.23 °C at Hakkari (EAN).

a) Mean temperature

Winter AutumnSpring Summer

b) Maximum temperature

c) Minimum temperature

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Figure 18. As in Figure 17, but for seasonal mean (a), maximum (b), and minimum (c) temperature series. Significance of trend rate isindicated with a pointed end

5.2.3. Trend rates in minimum temperature series. Most annual minimum temperatures have increased inTurkey (Figure 17(c)). Results of linear regression analysis show a significant warming at 29 stations andsignificant cooling only at two stations. Warming trends in 24 stations are significant at the 0.01 level.Significant linear night-time warming also exhibits a large spatial coherence over Turkey and trend rates perdecade are very high in all regions, except at some stations in the BLS and MAR regions. The maximumlinear warming occurs at Alanya (MED), with a rate of 0.56 °C per decade, which is significant at the 0.01level. The ranges of significant night-time warming rates per decade are as follows, according to the regions:0.13 to 0.23 °C in the BLS; 0.15 to 0.20 °C in the MAR; 0.08 to 0.25 °C in the AEG; 0.11 to 0.56 °C in theMED; 0.14 to 0.39 °C in the SAN; 0.11 to 0.29 °C in the CAN; and 0.11 to 0.34 °C in the EAN.

For winter minimum temperatures, even though most have tended to increase over the study period, only sixstations have a significant linear warming trend, three of which are located in the MED region (Figure 18(c)).Significant night-time cooling is found only for three stations. The highest night-time warming is at Kars(EAN), with a linear trend rate of 0.45 °C per decade. Significant warming rates vary from 0.17 to 0.32 °Cper decade in the MED region.

For spring minimum temperatures, the majority of the Turkish stations have shown a night-time warming(Figure 18(c)). Linear night-time warming trends are significant at 29 stations, 24 of which are at the 0.01level of significance. The highest night-time warming is found for Alanya (MED), with a trend rate of 0.49 °Cper decade at the 0.01 level. Ranges of significant warming trend rates per decade are as follows in regionalorder: 0.17 to 0.26 °C in the BLS; 0.20 to 0.29 °C in the MAR; 0.12 to 0.25 °C in the AEG; 0.21 to 0.49 °Cin the MED; 0.23 to 0.38 °C in the SAN; 0.13 to 0.32 °C in the CAN; and 0.23 to 0.34 °C in the EAN.

Summer minimum temperatures in Turkey have increased at the majority of the stations (Figure 18(c)).Linear warming trends are statistically significant at 34 stations, and 29 of those are at the 0.01 level. Stationshaving a significant warming trend cover a large area in Turkey, particularly over the western BLS andeastern MAR sub-regions, and AEG, MED and EAN regions. A significant cooling trend is found only fortwo stations of the EAN region. The highest night-time warming is seen at Alanya (MED), with a trend rateof 0.71 °C per decade, which is at the 0.01 level. Ranges of significant warming trend rates per decade aresummarized as follows for the regions: 0.17 to 0.30 °C in the BLS; 0.16 to 0.41 °C in the MAR; 0.17 to0.44 °C in the AEG; 0.12 to 0.71 °C in the MED; 0.20 to 0.60 °C in the SAN; 0.11 to 0.40 °C in the CAN;and 0.11 to 0.42 °C in the EAN.

Autumn minimum temperatures show both increasing and decreasing trends (Figure 18(c)). Significant linearwarming trends are found for series of the 15 stations, from which 11 are significant at the 0.01 level, whereasten stations have significant cooling trends. Significant cooling trends are more pronounced for the BLS region,with a total number of five stations having a range of trend rate from −0.16 to −0.33 °C per decade. As inannual and other seasonal minimum temperature series, the highest significant night-time warming exists atAlanya (MED), with a trend rate of 0.70 °C per decade. Ranges of significant warming rates per decade areas follows for the geographical regions: 0.13 to 0.23 °C in the AEG; 0.26 to 0.70 °C in the MED; 0.16 to0.37 °C in the SAN; 0.15 to 0.20 °C in the CAN; and 0.19 to 0.22 °C in the EAN.

6. SUMMARY AND CONCLUSIONS

The following gives a summary of the results and the main conclusions.(1) Mean temperatures. Year-to-year variations in annual mean temperature series of Turkey are generally

characterized by a PSC coefficient. Significant warming trends from the M–K test have shown up particularlyat the highly urbanized stations of the MED and SAN regions. The significant warming trend rates from theleast-squares linear regression vary between 0.07 and 0.34 °C per decade.

Most spring mean temperature series show an increasing trend. Summer mean temperature series aremostly characterized by a statistically significant PSC coefficient. Summer mean temperature series haveshown a slight warming at many stations over the western part of Turkey, whereas the rest of the countryhas experienced a general cooling. Autumn mean temperatures have significantly decreased at ten stations.Significant cooling trends are evident over the BLS region and the middle part of the EAN region. Significantlinear trend rates in the BLS region vary between −0.13 and −0.27 °C per decade. Kutiel and Maheras (1998)found a cooling trend in autumn over the eastern Mediterranean basin, and they attributed this cooling to anincrease in the northerly meridional circulation over that region. Cooling trends over the northern regions ofTurkey in autumn may have been associated with the increased northerly circulation.

(2) Maximum temperature series. The observed low-frequency fluctuations in annual maximum temperatureseries of Turkey are mostly associated with a significant PSC coefficient. A weak increasing trend shows upover the western and eastern regions of the country, and a decreasing trend is generally observed in the CANregion.

Year-to-year variability of spring maximum temperatures is mostly characterized by an insignificant negativeserial correlation coefficient. Spring maximum temperature series have indicated an increase at many stationsexcept those in the CAN region. Significant PSC coefficients at 42 stations are a statistical indication of theobserved low-frequency fluctuations in summer maximum temperature series. Summer maximum temperatureshave increased at many stations and decreased at some stations. Warming trends are significant at ninestations. Autumn maximum temperatures have decreased slightly over the BLS, MAR and CAN regions andsoutheastern corner of the EAN region.

(3) Minimum temperature series. Year-to-year variations of annual minimum temperatures indicate mostlya significant serial dependence. Most of the rapidly urbanizing and already urbanized stations of Turkeyhave experienced a night-time warming during the study period, and the warming trends at 31 stations aresignificant. The range of significant night-time warming rates is 0.08 to 0.56 °C per decade.

Year-to-year variations of most spring minimum temperatures are explained with the PSC coefficients.Spring minimum temperatures have shown a warming trend at the majority of the Turkish stations, 30 of

which are significant. The significant night-time warming trends dominate mainly in the highly urbanizedor rapidly urbanizing cities of Turkey, and significant warming rates lie within the range of 0.12 to 0.49 °Cper decade. Interannual variations of summer minimum temperature series at 58 stations are characterized bya significant PSC coefficient. As in spring, the summer temperatures have increased at the majority of thestations, most of which are located in the already urbanized or rapidly urbanizing cities. Warming trends aresignificant at 33 stations. The significant night-time warming rates are in the range of 0.11 to 0.71 °C perdecade. Autumn minimum temperature series have shown a significant warming trend at 16 stations, manyof which are located in the western and southern regions of the country. The range of significant warmingrates is 0.13 to 0.70 °C per decade. Cooling trends are evident at the stations of the northern Marmara, easternBLS and mid-northern EAN sub-regions, ten of which are significant.

(4) Overall assessment. Summer minimum temperatures have generally increased at a larger rate thanin spring and autumn minimum temperatures. On the other hand, night-time warming rates of spring andsummer are generally stronger than those that exist in spring and summer daytime temperatures. Consideringthe significant increasing trends in annual, spring and summer temperatures, it is seen that night-time warmingrates are stronger in the AEG, MED and SAN regions, which are characterized by the Mediterranean macro-climate type: a very hot and dry summer, a relatively hot and dry late spring and early autumn, and a rainywinter. We have seriously considered the strong warming trends in spring and summer and thus likely inannual minimum air temperatures. It is very likely that significant and very rapid night-time warming trendsover much of the country can be related to the widespread, rapid and increased urbanization in Turkey, inaddition to long-term and global effects of the human-induced climate change on air temperatures.

ACKNOWLEDGEMENTS

We would like to thank two anonymous referees for their constructive recommendations, and to express ourspecial thanks to Yurdanur Turkes of the TSMS for reviewing the manuscript.

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RE-EVALUATION OF TRENDS AND CHANGES IN MEAN, MAXIMUM AND MINIMUM TEMPERATURES OF TURKEY FOR THE...

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